Quality characteristics of registered cultivars and advanced lines of durum wheats grown in different ecological regions of Turkey
Bibliographic record
Abstract
Sakin, M. A., Sayaslan, A., Duzdemir, O. and Yuksel, F. 2011. Quality characteristics of registered cultivars and advanced lines of durum wheats grown in different ecological regions of Turkey. Can. J. Plant Sci. 91: 261–271. In this study, pasta-quality-associated characteristics of 25 durum wheat genotypes were investigated. Durum wheat genotypes consisted of 13 advanced experimental lines and 12 registered cultivars that were grown in three different locations of Turkey for 2 yr. Genotype, location, year and their interactions were found to be statistically significant in terms of all investigated quality characteristics. Mean quality parameters for the genotypes varied as follows: yellowberry kernel 1.7–6.1%, pigment content 3.67–8.31 mg kg −1 , lipoxygenase (LOX) activity 12.9–27.9 EU g −1 , protein content 10.8–11.8% (14% mb), gluten index (GI) 12-61, sodium dodecyl sulphate-sedimentation volume 17.3–28.7 mL, specific sedimentation volume 1.60–2.52 mL. Of the genotypes, 10 contained γ-gliadin 45 and six γ-gliadin 42 proteins. Except for Zenit, none of the registered cultivars and advanced experimental lines investigated in this study were able to meet simultaneously the requirements for high-quality pasta products; yet certain experimental lines prevailing in specific quality characteristics, such as Line-Gdem-2, Line-Gdem-12 and Line-20, may be used for further breeding purposes. The results of this study also imply that grain yield and quality should be taken collectively into consideration in wheat breeding programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".